AI Project Assistant
Keep projects on track with automatic status, risk flags, and workload balance.
- Project range
- $6,000–13,000
- AWS running cost
- $50–240/mo
- Time to deploy
- 3–5 weeks
- Best-fit industries
- Agencies, Consulting
Executive summary
A project assistant that reads from your existing tools to produce clear status updates, surface at-risk tasks before they slip, and highlight workload imbalances across the team. It answers 'where do things stand?' instantly, drafts client- and executive-ready summaries, and keeps managers focused on decisions instead of status wrangling.
Business problem
Project status lives in scattered tasks, chats, and spreadsheets, so managers spend hours assembling updates that are stale by the time they're shared. Risks surface late, overloaded team members go unnoticed, and clients get inconsistent visibility — leading to overruns and eroded trust.
Architecture
AWS services
Amazon API Gateway
Networking- — Query and reporting endpoint
- — Rate limiting
AWS Lambda
Compute- — Aggregate project data and generate updates
- — Trigger digests and alerts
Amazon Bedrock
AI / ML- — Draft status and client-ready summaries
- — Explain risks and recommend actions
Risk + workload model
Compute- — Predict slippage from progress and dependencies
- — Detect over- and under-allocation
Amazon DynamoDB
Database- — Project, task, and resource state
Amazon S3
Storage- — Generated reports and historical snapshots
Amazon EventBridge
Messaging- — Schedule digests and risk alerts
PM / messaging adapters
Integration- — Pull from project tools; deliver updates to Slack and email
Amazon CloudWatch
Observability- — Logs, metrics, and cost alarms
Data flow
- 1
The assistant pulls tasks, timelines, and assignments from your project tools into DynamoDB.
- 2
The risk and workload model predicts slippage and flags over- or under-allocated team members.
- 3
Bedrock drafts status updates and client-ready summaries and explains the top risks.
- 4
On a schedule, EventBridge delivers digests to Slack and email; reports are archived in S3.
- 5
Managers can ask 'where do things stand?' any time and get an instant, grounded answer.
Security considerations
- Project and client data encrypted at rest and in transit.
- Role-based access to projects and reports.
- Least-privilege IAM; PM-tool credentials in Secrets Manager.
- Summaries are grounded in source data and reviewable before sharing.
Cost considerations
- Bedrock summary and risk generation is the main variable cost.
- Scheduled digests batch the work to keep cost predictable.
- DynamoDB, S3, and EventBridge are inexpensive at rest.
Scalability
- Serverless throughout; scales across portfolios of projects.
- New project tools attach as adapters.
- Risk thresholds and report templates configurable per team and client.
Deployment roadmap
Phase 1 — Connect & templates
Week 1- — Connect project tools and define report templates
- — Provision AWS foundation
Phase 2 — Build & integrate
Weeks 2–4- — Build status generation and risk/workload model
- — Wire digests to Slack and email
Phase 3 — Pilot & tune
Week 5- — Pilot on active projects
- — Tune risk sensitivity and summary style
Future enhancements
- Predictive delivery-date and budget forecasting.
- Automated meeting-note-to-task capture (with Meeting Intelligence).
- Client-facing status portal.
- Portfolio health and utilization analytics into the executive dashboard.